GMM Selector-Based Anomaly Detection Model for Networks

Ensemble models for network anomaly detection are often challenged by class imbalance, a condition known to substantially degrade predictive accuracy. To address this limitation, a novel ensemble learning framework, termed the GMM Selector for Anomaly Detection (GMM-SAD), is proposed. The GMM-SAD fr...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:IEEE Access
المؤلفون الرئيسيون: Xinyu Guo, Jun He, Tao Jiang, Sunyan Hong, Jing Yu
التنسيق: مقال
اللغة:الإنجليزية
منشور في: IEEE 2025-01-01
الموضوعات:
Anomaly detection
class imbalance
network traffic
transformer
الوصول للمادة أونلاين:https://ieeexplore.ieee.org/document/11129045/

الانترنت

https://ieeexplore.ieee.org/document/11129045/

مواد مشابهة